The RWTH System for Statistical Translation of Spoken Dialogues

The RWTH System for Statistical Translation of Spoken Dialogues H. Ney, F. J. Och, S. Vogel Lehrstuhl f¨ur Informatik VI, Computer Science Department RWTH Aachen, University of Technology D-52056 Aachen, Germany ABSTRACT This paper gives an overview of our work on statistical ma- chine translation of spoken dialogues, in particular in the framework of the Verbmobil project. The goal of the Verbmobil project is the translation of spoken dialogues in the domains of appointment scheduling and travel plan- ning. Starting with the Bayes decision rule as in speech recognition, we show how the required probability distri- butions can be structured into three parts: the language model, the alignment model and the lexicon model. We describe the components of the system and report results on the Verbmobil task. The experience obtained in the Verbmobil project, in particular a large-scale end-to-end evaluation, showed that the statistical approach resulted in significantly lower error rates than three competing transla- tion approaches: the sentence error rate was 29% in compar- ison with 52% to 62% for the other translation approaches. 1. INTRODUCTION In comparison with written language, speech and espe- cially spontaneous speech poses additional difficulties for the task of automatic translation. Typically, these difficul- ties are caused by errors of the recognition process, which is carried out before the translation process. As a result, the sentence to be translated is not necessarily well-formed from a syntactic point-of-view. Even without recognition errors, speech translation has to cope with a lack of conventional syntactic structures because the structures of spontaneous speech differ from that of written language. The statistical approach shows the potential to tackle these problems for the following reasons. First, the statisti- cal approach is able to avoid hard decisions at any level of the translation process. Second, for any source sentence, a translated sentence in the target language is guaranteed to be generated. In most cases, this will be hopefully a syn- tactically perfect sentence in the target language; but even if this is not the case, in most cases, the translated sentence will convey the meaning of the spoken sentence. . Whereas statistical modelling is widely used in speech recognition, there are so far only a few research groups that apply statistical modelling to language translation. The pre- sentation here is based on work carried out in the framework of the EuTrans project [8] and the Verbmobil project [25]. 2. STATISTICAL DECISION THEORY AND LINGUISTICS 2.1 The Statistical Approach The use of statistics in computational linguistics has been extremely controversial for more than three decades. The controversy is very well summarized by the statement of Chomsky in 1969 [6]: “It must be recognized that the notion of a ‘probability of a sentence’ is an entirely useless one, under any interpretation of this term”. This statement was considered to be true by the major- ity of experts from artificial intelligence and computational linguistics, and the concept of statistics was banned from computational linguistics for many years. What is overlooked in this statement is …

Content truncated to 500 words